What is it about?
The objective of this paper is to present the geothermal heat flow model AFQ over continental Africa, based on random forest regression.
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Why is it important?
The study tries to address the challenges encountered with direct GHF measurements in Africa, namely, sparsity, non-uniformity, and uncertainty. Due to this limitation, estimates of continental GHF are derived indirectly from various geophysical and geological quantities. Conventional ways to address these issues, e.g., by implementing physics-based models, require various simplifications and are feasible only for few geophysical observables. The ability of the model to predict GHF values has been discussed and compared to several models trained with a different number of observables.
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This page is a summary of: A geothermal heat flow model of Africa based on random forest regression, Frontiers in Earth Science, September 2022, Frontiers, DOI: 10.3389/feart.2022.981899.
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